Facing the market uncertainty, information flow plays an important role in determining supply chain performance. In particular, demand information is a type of information that is often available and widely used in supply chain practices. Effective acquisition and management of demand information can lead to excellence in supply chain management....[ Read more ]

Facing the market uncertainty, information flow plays an important role in determining supply chain performance. In particular, demand information is a type of information that is often available and widely used in supply chain practices. Effective acquisition and management of demand information can lead to excellence in supply chain management.

In this thesis, we begin with studying the effects of two information acquisition approaches in a setting of new product introduction: one is the scheduled approach, and the other is the adaptive approach. We derive the optimal policies for both approaches and compare their performances. We identify situations in which the adaptive approach yields a significant profit advantage over the scheduled one.

We then study demand information acquisition in a setting of competing firms. Specifically, we find that a firm’s decision on information acquisition depends on others’ decisions in the presence of horizontal competition. Via a game-theoretic framework, we demonstrate how decentralized decision making affects the information acquisition level and how the level depends on various parameters.

Quick Response is a strategy commonly used in practice to hedge against demand uncertainty. We study how the Quick Response can improve assortment planning in supply chain management. We compare the optimal profits with and without Quick Response for a supply chain consisting of an apparel supplier and a buyer.